Method for parameter selection on the basis of migration law of injected gas for condensate gas reservoir and apparatus

Abstract

The present invention relates to the field of oil exploration, in particular to a method for parameter selection on the basis of the migration law of an injected gas for a condensate gas reservoir and an apparatus. The method comprises: according to an injection condition set, constructing a mathematical model for the flow and diffusion of an injected fluid; numeralizing the mathematical model, so as to obtain a relationship curve between a breakthrough time of an injected gas and the Peclet number; constructing a physical simulation model for the displacement of a condensate gas reservoir by the injected fluid, and on the basis of an injection condition, carrying out a condensate gas reservoir simulation experiment, so as to obtain a simulation result; according to the simulation result, verifying and fitting the relationship curve between the breakthrough time of the injected gas, the mobility ratio and the Peclet number, so as to determine a breakthrough time calculation formula; by means of using injection parameter sets, performing condensate gas reservoir gas injection experiments, and calculating the breakthrough time of the condensate gas reservoir gas injection experiment corresponding to each injection parameter set; and determining as optimal injection parameters the injection parameter set corresponding to the condensate gas reservoir gas injection experiment with the shortest breakthrough time. The present solution solves the problem of blockages of oil and gas seepage flow channels of condensate gas reservoirs, thus preventing affects on normal operations of oil and gas wells.

Description

Parameter selection method and device based on gas injection migration law of condensate gas reservoir

[0001] The present invention claims priority to Chinese patent application No. 2023113531417, filed on October 18, 2023, entitled “Parameter selection method and device based on gas injection and migration law of condensate gas reservoirs”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present invention relates to the field of petroleum exploration, in particular to a parameter selection method and device based on gas injection migration law of condensate gas reservoirs. Background Art

[0003] Condensate gas reservoirs are a common phenomenon in the exploration and production of oil and gas reservoirs. Specifically, when hydrocarbon gas under high temperature and high pressure conditions deep underground is extracted to the surface, liquid petroleum will condense due to the decrease in temperature and pressure. This liquid light oil is condensate oil, and this gas reservoir is a condensate gas reservoir.

[0004] Currently, condensate gas reservoirs containing highly saturated condensate oil accumulate near the wellbore, easily blocking oil and gas flow pathways and severely impacting oil and gas production efficiency. Furthermore, condensate gas reservoirs typically exhibit high temperature and high pressure, making it difficult to visualize gas flow through porous media.

[0005] Currently, the industry generally uses dry gas stripped of condensate as an injectant for dredging oil and gas seepage channels near the wellbore. Injecting gas into condensate reservoirs requires determining injection parameters. Existing methods typically determine these parameters based on actual injection experience. This results in a complex process and inaccurate parameters, severely impacting the efficiency of dredging oil and gas seepage channels.

[0006] Summary of the Invention

[0007] To solve the problem in the prior art that gas injection parameters are determined based on operational experience, which affects the efficiency of clearing oil and gas seepage channels, the embodiments of this article provide a parameter selection method and device based on the migration law of gas injection in condensate gas reservoirs.

[0008] According to one aspect of an embodiment of the present specification, the method includes: constructing a mathematical model of the flow and diffusion of the injected fluid based on an injection condition set; digitizing the mathematical model of the flow and diffusion of the injected fluid to obtain a relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Peclet number; constructing a physical simulation model for the injected fluid to displace the condensate gas reservoir, and based on the physical simulation model, conducting a condensate gas reservoir simulation experiment according to the injection conditions to obtain simulation results; based on the simulation results, verifying and fitting the relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Peclet number to determine a breakthrough time calculation formula; using an injection parameter set, conducting a condensate gas reservoir injection experiment based on the physical simulation model of the injected fluid to displace the condensate gas reservoir, and using the breakthrough time calculation formula to calculate the breakthrough time of the condensate gas reservoir injection experiment corresponding to each set of injection parameter sets; determining the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

[0009] The embodiments of this specification also provide a parameter selection device based on the migration law of gas injection in a condensate gas reservoir, the device comprising: a mathematical model construction unit for constructing a mathematical model of the flow and diffusion of the injected fluid based on injection conditions, wherein the injection conditions include: the properties of the injection medium and the diffusion and convection of the injected fluid; a relationship curve determination unit for digitizing the mathematical model of the flow and diffusion of the injected fluid to obtain a relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Péclet number; a physical simulation model construction unit for constructing a physical simulation model for the injection fluid to displace the condensate gas reservoir, and conducting a condensate gas reservoir experiment under the injection conditions based on the physical simulation model to obtain simulation results; a breakthrough time calculation unit for verifying the fitting of the mobility ratio and the Péclet number based on the simulation results and the relationship curve to determine a breakthrough time calculation formula; an experimental unit for conducting a gas injection experiment in a condensate gas reservoir using an injection parameter set, and calculating the breakthrough time of the condensate gas reservoir gas injection experiment corresponding to each set of injection parameter sets using the breakthrough time calculation formula; and an optimal injection parameter determination unit for determining the injection parameter set corresponding to the condensate gas reservoir gas injection experiment with the shortest breakthrough time as the optimal injection parameter.

[0010] An embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for measuring breakthrough pressure of dense rock is implemented.

[0011] The embodiments of this document further provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for measuring the breakthrough pressure of dense rock is implemented.

[0012] This solution solves the problem of condensate gas reservoirs blocking oil and gas seepage channels to avoid affecting the normal operation of oil and gas wells, reduces the decline in old areas, increases recoverable reserves, converts underground resources into production, and produces better economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of this article or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of this article. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0014] FIG1 is a flow chart of a parameter selection method based on the migration law of gas injection in a condensate gas reservoir according to an embodiment of this specification;

[0015] FIG2 is a flow chart of a method for constructing an injection gas flow and diffusion model according to this specification;

[0016] FIG3 is a flow chart of a method for determining a relationship curve between the breakthrough time of injected gas and the mobility ratio and the Péclet number according to an embodiment of the present specification;

[0017] FIG4 is a flow chart showing a method for constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir according to an embodiment of this specification;

[0018] FIG5 is a flow chart of a method for verifying the relationship between the fitted breakthrough time, mobility ratio, and Péclet number according to an embodiment of this specification;

[0019] FIG6 is a schematic diagram showing the structure of a parameter selection device based on the migration law of gas injection in a condensate gas reservoir according to an embodiment of this invention;

[0020] 7A and 7B are schematic diagrams showing a mathematical model of flow and diffusion of an injected fluid according to an embodiment of this specification;

[0021] FIG8 is a schematic diagram of the viscosity finger diameter under a constant diffusion coefficient in an embodiment of this specification;

[0022] FIG9 is a schematic diagram showing the viscosity finger diameter when the mobility ratio is 1.5 according to an embodiment of this specification;

[0023] FIG10 is a schematic diagram showing the viscosity finger diameter when the mobility ratio is 2 according to an embodiment of this specification;

[0024] FIG11 is a schematic diagram of the viscosity finger diameter when the mobility ratio is 2.5 according to an embodiment of this specification;

[0025] FIG12 is a schematic diagram showing the viscosity finger diameter when the Péclet number is 300 according to an embodiment of this specification;

[0026] FIG13 is a schematic diagram showing the viscosity finger diameter when the Péclet number is 500 according to an embodiment of this specification;

[0027] FIG14 is a schematic diagram showing the viscosity finger diameter when the Péclet number is 900 according to an embodiment of this specification;

[0028] FIG15 is a schematic diagram showing a breakthrough time and Peclet relationship curve according to an embodiment of this specification;

[0029] FIG16 is a schematic diagram showing the structure of a computer device according to an embodiment of this invention.

[0030] Explanation of the symbols in the accompanying drawings: 601, mathematical model construction unit; 602, relationship curve determination unit; 603, physical simulation model construction unit; 604, breakthrough time calculation unit; 605, experimental unit; 606, optimal injection parameter determination unit; 1602, computer equipment; 1604, processor; 1606, memory; 1608, driving mechanism; 1610, input / output module; 1612, input device; 1614, output device; 1616, presentation device; 1618, graphical user interface; 1620, network interface; 1622, communication link; 1624, communication bus. DETAILED DESCRIPTION

[0031] In order to help those skilled in the art better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of this specification.

[0032] It should be noted that the terms "first," "second," and the like in the specification and claims herein and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0033] This specification provides method operation steps as described in the embodiments or flowcharts, but more or fewer operation steps may be included based on routine or non-creative work. The order of steps listed in the embodiments is only one way of executing the steps among many orderings and does not represent the only execution order. When a system or device product is actually executed, the method can be executed in the order shown in the embodiments or the drawings or in parallel.

[0034] It should be noted that the parameter selection method based on the migration law of gas injection in condensate gas reservoirs in this article can be used in the field of oil and gas field exploration. This article does not limit the application field of the parameter selection method and device based on the migration law of gas injection in condensate gas reservoirs.

[0035] FIG1 is a flow chart of a parameter selection method based on the migration law of gas injection in a condensate gas reservoir according to an embodiment of this specification, which specifically includes the following steps:

[0036] Step 101: A mathematical model of the flow and diffusion of the injected fluid is constructed based on a set of injection conditions. In this step, the set of injection conditions includes the properties of the injected fluid and the diffusion and convection states of the injected fluid. The injected fluid properties include, but are not limited to, the type of injected fluid, the viscosity of the injected fluid, and the density of the injected fluid.

[0037] In this step, a mathematical model of the flow and diffusion of the injected fluid is constructed by taking into account factors such as gravity, the type of medium of the injected fluid, and the convection and diffusion of the injected fluid. In this step, the injected fluid can be a gas, including but not limited to: methane, nitrogen, field gas, carbon dioxide, etc.

[0038] In the embodiments of this specification, since the migration of injected gas in the condensate gas field is mainly affected by displacement force and gravity, the basic model of the mathematical model of injected fluid flow and diffusion adopts the Hele-Shaw model.

[0039] In the examples of this specification, if the effect of gravity on injected gas migration is not considered, and the basic model is a two-dimensional homogeneous medium with no phase change or heat conduction, a constant diffusion coefficient, complete miscibility, single-phase flow, and the same velocity at the outlet and inlet, the migration of the injected gas is described by the continuity equation, the momentum equation in the form of Darcy's law, and the convection-diffusion equation of concentration in the case of an incompressible Newtonian fluid.

[0040] Furthermore, after obtaining the basic model, due to the actual injection conditions of condensate gas fields, it is necessary to consider the gravity-induced gravity overburden and establish an injection fluid motion equation that includes gravity. This injection medium motion equation that includes gravity is more consistent with the actual migration of injected gas in condensate gas fields. Therefore, a mathematical model for the flow and diffusion of injected fluids was constructed based on the momentum equation based on Darcy's law, the convection-diffusion equation for concentration, and the gravity factor.

[0041] In this step, numerical simulation is used to describe the complex displacement process. The displacement process involves a fluid with lower viscosity replacing a fluid with higher viscosity. When the two fluids come into contact, a viscous fingering region is formed. The mathematical model used in this step calculates the width and state of the viscous fingering region at each moment of contact. This, in turn, determines the diffusion and convection state of the injected fluid, ultimately determining the displacement breakthrough time.

[0042] Step 102: digitize the mathematical model of the flow and diffusion of the injected fluid to obtain a relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Peclet curve.

[0043] In this step, the two key parameters describing the flow state of the injected fluid are mobility ratio and Péclet number. In this step, the momentum equation, the convection-diffusion equation of concentration, and the boundary conditions in the mathematical model of the flow and diffusion of the injected fluid are calculated to solve the migration of the injected gas under different injection speed conditions. Specifically, numerical calculations can calculate the viscosity index at different times under a constant diffusion coefficient, the viscosity index at different times under different mobility ratios, and the viscosity index at different times under different Péclet numbers. This is shown in Figures 8 to 14.

[0044] Step 103 constructs a physical simulation model for injecting fluid to displace a condensate reservoir. Based on this physical simulation model, a condensate reservoir simulation experiment is conducted according to the injection conditions to obtain simulation results. In the embodiments of this specification, the physical simulation model for injecting fluid to displace a condensate reservoir is used to simulate a real-world downhole scenario containing a condensate reservoir. Experiments are conducted using a set of injection conditions to ultimately obtain simulation results. These simulation results represent the breakthrough time required for the injected fluid to completely displace the condensate gas after injecting different types of fluids.

[0045] In the examples of this specification, a displacement experiment is conducted by injecting fluid into the experimental device to determine the injection conditions such as the injection rate, injection pressure, temperature, type of injected fluid, and fluid viscosity at the initial moment. Displacement is achieved by convection and diffusion between the injected fluid and the originally existing condensate gas, and the time it takes for the injected fluid to break through the entire device is recorded. Therefore, the simulation result is the breakthrough time of the injected fluid in the experiment.

[0046] Step 104 : verifying the relationship between the breakthrough time of the injected fluid, the mobility ratio, and the Péclet number based on the simulation results and the relationship curve, and determining a breakthrough time calculation formula.

[0047] In the examples of this specification, under normal circumstances, the breakthrough time of the injected fluid calculated through numerical simulation using a numerical mathematical model of the flow and diffusion of the injected fluid should be consistent with or have a small difference from the breakthrough time obtained through physical simulation. Therefore, using a physical simulation model of the injected fluid displacing a condensate gas reservoir, the simulation results obtained through the experiment are fitted to the relationship between the breakthrough time calculated from the mathematical model of the flow and diffusion of the injected fluid, the mobility ratio, and the Péclet number, thereby obtaining an accurate formula for calculating the breakthrough time.

[0048] In the embodiments of this specification, a mathematical model of injected fluid flow and diffusion is used to numerically simulate the complex displacement process. The numerical simulation results of the mathematical model are verified by combining the physical simulation model of injected fluid displacement of condensate gas reservoirs to improve the prediction ability of the displacement process.

[0049] In the embodiments of this specification, the formula for calculating the breakthrough time of the injected gas can also be used to determine the appropriate mobility ratio or Péclet number to achieve the desired breakthrough time. The mobility ratio and Péclet number can be converted into other adjustable injection parameters. Therefore, optimal injection parameters can be determined based on the inferred mobility ratio or Péclet number.

[0050] Step 105 utilizes the injection parameter set and, based on the physical simulation model of the injected fluid displacing the condensate gas reservoir, conducts a gas injection experiment into the condensate gas reservoir. The breakthrough time calculation formula is used to calculate the breakthrough time for each gas injection experiment corresponding to each injection parameter set. In this step, the injection parameter set from step 101 can be used to conduct an actual experiment displacing the condensate gas reservoir with injected gas. The breakthrough time calculation formula for the injected gas determined in the previous step is used to calculate the breakthrough time for each physical simulation experiment. In other embodiments of this specification, other injection parameter sets may also be selected for the physical simulation experiment.

[0051] Step 106: Determine the injection parameter set corresponding to the condensate gas reservoir experiment with the shortest breakthrough time as the optimal injection parameter set. In this step, the physical time of the condensate gas reservoir with the shortest breakthrough time is determined as the optimal experiment, and the injection parameter set corresponding to this experiment is determined as the optimal parameter set.

[0052] FIG2 is a flow chart of a method for constructing an injected gas flow diffusion model in this specification. In the embodiment of this specification, the injection condition set includes: fluid velocity, viscosity, diffusion coefficient, concentration, flow function, etc. of the injected fluid. The method specifically includes the following steps:

[0053] Step 201: construct a kinetic equation of the injected fluid based on the fluid velocity, viscosity, and diffusion coefficient of the injected fluid. Specifically, the kinetic equation is expressed as follows:

[0054] Where p' = p / (μ1·D·K-1) represents the pressure, U represents the velocity field of the injected fluid, D represents the diffusion coefficient tensor, μ' = μ / μ1 represents the dimensionless fluid viscosity, u' = u / U represents the dimensionless fluid velocity, μ1 represents the viscosity of the injected fluid, K represents the permeability of the injected fluid, and μ represents the fluid viscosity.

[0055] In the examples of this specification, in the application process of gas injection into condensate gas reservoirs where gravity differentiation is obvious, the effect of gravity cannot be ignored. Therefore, the kinetic equations of the examples of this specification take gravity into account. When considering gravity, the kinetic equation is constructed as shown in the following formula:

[0056] p represents pressure, u represents the velocity field of the injected fluid, μ / K represents the fluid mobility of the injected fluid, ρ represents density, g represents the acceleration due to gravity, and x and y represent the two-dimensional coordinate systems in the mathematical model. The velocity field of the fluid refers to the vector velocity distribution at the fluid flow front. This refers to the distribution of the fluid velocity vector at all points in space at the same moment in time.

[0057] In addition, the mathematical model for the flow and diffusion of the injected gas also includes: constructing a continuity equation based on the injection velocity of the injected fluid, which is expressed as follows: Where u represents the injection velocity of the injected fluid, and x and y represent the two-dimensional coordinate system in the mathematical model.

[0058] Step 202: Construct a convection-diffusion equation for the fluid concentration based on the concentration and flow rate function of the injected fluid. In the embodiment of this specification, the convection-diffusion equation for the fluid concentration is expressed as follows:

[0059] Where c represents concentration, D represents diffusion coefficient, t represents time, and x and y represent the two-dimensional coordinate system in the mathematical model.

[0060] In some other embodiments of the present specification, the mathematical model of the flow and diffusion of the injected fluid also includes the Poisson equation: Where ω is the vorticity and ψ is the flow function.

[0061] Step 203: Perform dimensionless analysis on the kinetic equation and convection-diffusion equation. Since the kinetic equation and convection-diffusion equation cannot distinguish the influence of each parameter, the velocity, length, and time are dimensionlessly quantized as u'=u / U, L'=L / (D / U), and t'=t / (D / U2 squared). At the same time, the viscosity, density, and pressure are processed as μ'=μ / μ1, ρ'=ρ / ρ1, and p'=p / (μ1·D·K-1), and the mathematical model is dimensionlessly analyzed.

[0062] In this step, dimensionless processing is used to obtain the dimensionless equation of vorticity, as expressed in the following formula: Where u represents the velocity of the injected fluid, c' represents the dimensionless concentration of the injected fluid, μ represents the fluid viscosity, U represents the velocity field of the injected fluid, K represents the permeability of the injected fluid, x and y represent the abscissa and ordinate of the mathematical model of the flow and diffusion of the injected fluid, ρ1 represents the density of the injected fluid, ψ is the flow function, and g represents the acceleration of gravity.

[0063] After considering the total concentration in space, the one-dimensional convection-diffusion equation, and the interference concentration, the dimensionless equation obtained becomes:

[0064] In step 204, the flow variables in the dimensionless kinetic and diffusion equations are subjected to a Hartley transform to obtain a mathematical model for the flow and diffusion of the injected gas. After the Hartley transform, an alternating implicit method is used to solve for the concentrated concentration c and iterative pressure in the x-axis direction until both concentration c and pressure p converge. The y-axis is then iterated for dt / 2. After completing the x- and y-direction iterations, the mathematical model for the flow and diffusion of the injected gas is constructed.

[0065] FIG3 is a flow chart of a method for determining a relationship curve between the breakthrough time of injected gas and the mobility ratio and the Péclet number according to an embodiment of this specification, which specifically includes the following steps:

[0066] Step 301 : numerically solving a mathematical model of the flow and diffusion of the injected fluid, and determining the viscosity index diameter of the mathematical model of the flow and diffusion of the injected fluid at a constant diffusion coefficient at different times and the viscosity index diameter at a constant mobility ratio at different times.

[0067] In this step, the viscosity index of each grid of the two-dimensional plane of the mathematical model is numerically solved and calculated, and based on the correlation between each grid and other grids, a schematic diagram of the viscosity index of the entire two-dimensional plane of the mathematical model is finally drawn.

[0068] As shown in Figure 7A, the concentration field for a flow displacement with a constant diffusion coefficient initially exhibits no apparent instabilities, and a stable diffusion region exists at the contact. The width of the two-component region increases over time. This period, referred to as the diffusion-dominated period, is characterized by minimal instability. However, within dimensionless time intervals, such as t = 100 to 150, some small wave perturbations begin to develop. At t = 200, the recognizable contact region of the viscous finger becomes unstable. The evolution of the mixing region then switches to a convection-dominated period with a characteristic time Tc. Over the following time period, the initial finger undergoes a series of mechanisms, leading to the development of the finger and its merging with other fingers. Ultimately, several dominant fingers emerge, reaching the rightmost edge, with the boundary indicated at t = 500. Throughout the displacement-diffusion process, the viscous finger grows within a relatively thick transition region between the diffusion region and the contact region.

[0069] Step 302 : Determine a relationship curve between breakthrough time, mobility ratio, and Péclet number based on the viscosity index diameter at constant diffusion coefficients at different times and the viscosity index diameter at constant mobility ratios at different times.

[0070] As shown in Figure 11, as the mobility ratio R increases, the instability of the displacement front occurs earlier and the movement of the viscous fingering becomes more complex. For example, when the mobility ratio R is 1.5, the initial instability of the displacement front occurs at around time 400, while when the mobility ratio R is 3.0, the initial instability of the displacement front occurs at around time 200. For the case of a constant diffusion coefficient D, the change of R does not affect the diffusion coefficient, so it will be superimposed on the same P e It can be seen that the larger R is, the shorter the diffusion range is and the earlier the instability is triggered.

[0071] Figures 12 to 14 below show the viscosity finger diameter results under the same mobility ratio and different Peclet numbers. The mobility ratio R is 3. As can be seen from Figures 12, 13 and 14, as the Peclet number P e As the mobility ratio R increases, the frontal breakthrough time decreases.

[0072] For a fixed diffusion coefficient D and the length L of the porous medium, the larger the Péclet number P e This indicates that higher injection rates and more unstable flow rates cause the viscous finger to reach the downstream boundary more quickly. The breakthrough time and Péclet relationship curves are shown in Figure 15.

[0073] FIG4 is a flow chart of a method for constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir according to an embodiment of this specification, which specifically includes the following steps:

[0074] Step 401: Determine the condensate gas required for physical simulation based on the on-site well flow composition.

[0075] In the examples of this specification, in order to ensure the effect of the experimental simulation of the gas reservoir, the injection volume of the condensate gas in a single experiment shall not be less than 1.5 times the experimental amount. Use an injection pump to inject formation water into the two-dimensional model, and the injection volume is 1.5 times the pore volume to ensure that the gas reservoir formation water is configured in the container tank according to the ion concentration. Furthermore, based on the logistics components of the actual wells in the target work area, determine the compound condensate gas of the physical simulation model of the condensate gas reservoir to be displaced by the injected fluid. Among them, the compound condensate gas includes: the components in the condensate gas and the molar fraction of each component. As shown in Table 1 below:

[0076] Table 1 YH23-2-10 well flow composition and small model composite gas composition

[0077] Step 402 : According to the status of the on-site well and based on the principle of similarity between gravity and displacement force, determine the physical simulation injection-production pressure difference.

[0078] In this step, a reasonable injection-production pressure differential must be designed for the physical simulation model. Specifically, based on the cyclic injection development mechanism of condensate gas reservoirs, molecular diffusion is only related to temperature and pressure. Based on the similarity between the gravity and displacement force ratios in the oil field and the laboratory, the injection-production pressure differential for the physical simulation model is determined using the following calculation formula:

[0079] Where ρ is the gas density of condensate gas, expressed in kg / m³, g represents gravitational acceleration, h represents height, and p represents pressure. The injection-production pressure differential in the laboratory is further determined based on the height of the actual well in the oil field, the downhole pressure in the oil field, and the height of the laboratory physical simulation model.

[0080] In the embodiments of this specification, the density of condensate gas can be calculated according to an empirical formula, which is expressed as follows:

[0081] Where p is pressure; γg is gas specific gravity; T is temperature; and z is the gas deviation coefficient, which is dimensionless.

[0082] The above formula calculates that the density of condensate gas at 138°C and 54.94 MPa is 0.279 g / cm 3 The injection-production pressure difference of the physical simulation model was calculated based on the similarity ratio formula to be 6.94 kPa.

[0083] Step 403: Determine the injection rate of the injected fluid based on the injection-production pressure difference and Darcy's equation. After determining the injection-production pressure difference, calculate the injection rate based on Darcy's equation to be 1.5cc / min.

[0084] Step 404 , select different gas injection methods, injection fluid types, injection timings, injection pressures, and injection speeds to complete the construction of the physical simulation model.

[0085] In the embodiments of this specification, different gas injection methods for condensate gas reservoirs will have a serious impact on the recovery rate and final recovery rate of condensate gas and condensate oil. In order to study the best gas injection method for a condensate gas reservoir in a certain well in a certain work area, axial gas injection, top gas injection and bottom gas injection are selected for comparative analysis.

[0086] In the examples of this specification, the migration patterns of injected gas within a formation require consideration of the properties of the injected fluid. Because the properties of the reservoir fluid and the injected fluid (gas) differ significantly, the interaction between them can significantly affect the migration of the injected gas. Therefore, three injection media were selected for comparative analysis: methane, carbon dioxide, and in situ gas.

[0087] In the examples of this specification, in order to analyze the influence of injection timing on the recovery effect of condensate gas reservoirs, three gas injection methods are selected for comparative analysis, namely, depletion production, depletion to 38 MPa and then pressure increase to 58 MPa production, and depletion to 38 MPa and then pressure increase to 46 MPa production.

[0088] In the examples of this specification, in order to analyze the effect of injection pressure on the recovery effect of condensate gas reservoirs, three gas injection pressures are selected for comparative analysis, namely 58 MPa, 46 MPa and 38 MPa.

[0089] In the examples of this specification, in order to analyze the influence of injection rate on the recovery effect of condensate gas reservoir, three gas injection pressures are selected for comparative analysis, namely 0.05 ml / min, 0.1 ml / min and 0.15 ml / min.

[0090] By selecting different gas injection methods, injection media, injection timing, injection pressure and injection rate, experiments were carried out based on the physical simulation model of fluid displacement of condensate gas reservoirs.

[0091] FIG5 is a flow chart of a method for verifying the relationship between the fitted breakthrough time, mobility ratio, and Péclet number according to an embodiment of this specification, which specifically includes the following steps:

[0092] Step 501, fitting determines the relationship between dimensionless breakthrough time, mobility ratio, and Péclet number. Specifically, the following formula is used: BT =e 0.793419×e-0.231092R×Pe 0.899608 ; where t BT represents the dimensionless breakthrough time; R represents the mobility ratio, and Pe represents the Péclet number.

[0093] In this step, the mathematical model calculates the mobility ratio R and Péclet number Pe at each time point. Each mobility ratio R and Péclet number Pe at time t constitutes a point, which is connected to form a curve in two-dimensional coordinates. This curve is fitted with the test results of condensate gas reservoir simulation experiments based on the physical simulation model and injection conditions to obtain a dimensionless relationship formula between breakthrough time, mobility ratio, and Péclet number.

[0094] According to the description in step 104, based on the physical simulation model of the injected fluid to displace the condensate gas reservoir, the relationship between the injected gas breakthrough time, the mobility ratio and the Péclet number is verified and fitted, and the relationship between the injected gas breakthrough time, the mobility ratio and the Péclet number is adjusted so that the relationship between the gas breakthrough time, the mobility ratio and the Péclet number corresponds to the simulation results of the physical simulation model.

[0095] Step 502: Determine the breakthrough time. Specifically, the breakthrough time is determined according to the following formula:

[0096] Among them, t BT represents the dimensionless breakthrough time, t represents the breakthrough time, D represents the diffusion coefficient tensor, and U represents the injection velocity.

[0097] FIG6 is a schematic diagram of the structure of a parameter selection device based on the migration law of gas injection in a condensate gas reservoir according to an embodiment of the present invention. This figure describes the basic structure of the parameter selection device based on the migration law of gas injection in a condensate gas reservoir. The functional units and modules therein can be implemented in software, or a general chip or a specific chip can be used to select parameters based on the migration law of gas injection in a condensate gas reservoir. The device specifically includes:

[0098] The mathematical model building unit 601 is used to build a mathematical model of the flow and diffusion of the injected fluid according to the injection conditions, wherein the injection conditions include: properties of the injected medium and diffusion and convection of the injected fluid;

[0099] A relationship curve determination unit 602 is used to digitize the mathematical model of the flow and diffusion of the injected fluid to obtain the injection gas breakthrough time and mobility ratio and the Peclet relationship curve;

[0100] A physical simulation model building unit 603 is used to build a physical simulation model for injecting fluid to displace a condensate gas reservoir, and to perform a condensate gas reservoir experiment under the injection conditions based on the physical simulation model to obtain simulation results.

[0101] a breakthrough time calculation unit 604 for verifying and fitting the mobility ratio and the Péclet number based on the simulation results and the relationship curve, and determining a breakthrough time calculation formula;

[0102] The experimental unit 605 is used to perform a gas injection experiment in a condensate gas reservoir using the injection parameter set, and calculate the breakthrough time of the gas injection experiment in the condensate gas reservoir corresponding to each set of injection parameter sets using the breakthrough time calculation formula;

[0103] The optimal injection parameter determination unit 606 is configured to determine the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

[0104] This plan aims to sustainably and efficiently develop existing condensate oil and gas fields, reducing decline in older areas, increasing recoverable reserves, and converting underground resources into production, generating significant economic benefits. It also comprehensively enhances the development technology of condensate gas reservoirs. It improves mid- to late-stage cyclic gas injection to enhance oil recovery, innovates and breaks through mid- to late-stage depletion development techniques for condensate gas reservoirs with oil rims, and explores how to increase condensate oil recovery in late-stage reserve development near abandonment pressures.

[0105] Figures 7A and 7B are schematic diagrams of a mathematical model of the flow and diffusion of an injected fluid according to an embodiment of this specification. The mathematical model shown in the figure is a two-dimensional mathematical model. The length of the two-dimensional mathematical model is L and the height is H. The injected fluid of the mathematical model is a two-dimensional horizontally flowing uniform porous medium, and its displacement length can reach L. The injected fluid injects a condensate gas with a viscosity of μ1 and a displacement viscosity of μ2 at a slow and stable speed U. The concentration of the injected gas is c1 and the viscosity is μ1, and the concentration of the condensate gas is c2 and the viscosity is μ2. The velocity field of the injected gas is U, which changes with time, and the velocity field is expressed as U(t).

[0106] Figure 8 shows a schematic diagram of the viscosity finger diameter under a constant diffusion coefficient scenario according to an embodiment of this specification. As can be seen, the concentration field for flow displacement with a constant diffusion coefficient initially exhibits no significant instability, and a stable diffusion region exists at the contact point. Over time, the width of the two component regions increases, forming a diffusion-dominated period. The unstable portion during the diffusion-dominated period is minimal.

[0107] Figure 9 shows a schematic diagram of the viscosity finger diameter for a mobility ratio of 1.5 according to an embodiment of this specification, Figure 10 shows a schematic diagram of the viscosity finger diameter for a mobility ratio of 2 according to an embodiment of this specification, and Figure 11 shows a schematic diagram of the viscosity finger diameter for a mobility ratio of 2.5 according to an embodiment of this specification. As shown in Figures 9, 10, and 11, as the mobility ratio R increases, the instability of the displacement front occurs earlier, and the movement of the viscous finger becomes more complex.

[0108] FIG12 is a schematic diagram of the viscosity index diameter when the Peclet number is 300 according to an embodiment of the present specification, FIG13 is a schematic diagram of the viscosity index diameter when the Peclet number is 500 according to an embodiment of the present specification, and FIG14 is a schematic diagram of the viscosity index diameter when the Peclet number is 900 according to an embodiment of the present specification. In FIG12, FIG13 and FIG14, the mobility ratio R is 3. As the Peclet number P increases, the viscosity index diameter increases. e With the increase of , the leading edge breakthrough time has an overall trend of increasing.

[0109] Figure 15 shows a curve diagram of the relationship between breakthrough time and Peclet number according to an embodiment of this specification. As can be seen from the figure, when the mobility ratio remains unchanged, the larger the Peclet number, the longer the breakthrough time.

[0110] As shown in FIG16 , a computer device according to an embodiment of the present invention is implemented by the computer device for performing the parameter selection method based on the migration patterns of gas injection in condensate gas reservoirs. The computer device 1602 may include one or more processors 1604, such as one or more central processing units (CPUs), each of which may implement one or more hardware threads. The computer device 1602 may also include any memory 1606 for storing any type of information, such as code, settings, and data. For example, and without limitation, the memory 1606 may include any one or more combinations of the following: any type of RAM, any type of ROM, a flash memory device, a hard disk, an optical disk, and the like. More generally, any memory may use any technology to store information. Furthermore, any memory may provide volatile or non-volatile retention of information. Furthermore, any memory may represent a fixed or removable component of the computer device 1602. In one embodiment, when the processor 1604 executes associated instructions stored in any memory or combination of memories, the computer device 1602 may perform any operation of the associated instructions. The computer device 1602 also includes one or more drive mechanisms 1608 for interacting with any storage, such as a hard disk drive mechanism, an optical disk drive mechanism, and the like.

[0111] The computer device 1602 may also include an input / output module 1610 (I / O) for receiving various inputs (via input devices 1612) and for providing various outputs (via output devices 1614). A specific output mechanism may include a presentation device 1616 and an associated graphical user interface (GUI) 1618. In other embodiments, the input / output module 1610 (I / O), input devices 1612, and output devices 1614 may not be included, and the computer device 1602 may simply be a computer device in a network. The computer device 1602 may also include one or more network interfaces 1620 for exchanging data with other devices via one or more communication links 1622. One or more communication buses 1622 couple the components described above together.

[0112] Communication link 1623 may be implemented in any manner, for example, via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. Communication link 1622 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0113] Corresponding to the methods in FIG. 1 to FIG. 5 , the embodiments of this document further provide a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above method are executed.

[0114] The embodiments of this document also provide a computer-readable instruction, wherein when a processor executes the instruction, the program therein causes the processor to execute the method shown in Figures 1 to 5.

[0115] It should be understood that in the various embodiments of this document, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this document.

[0116] It should also be understood that in the embodiments herein, the term "and / or" merely describes an association between associated objects, indicating that three possible relationships exist. For example, "A and / or B" could represent: A alone, A and B simultaneously, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0117] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this document.

[0118] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0119] In the several embodiments provided herein, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units described is merely a logical functional division. In actual implementation, other division methods may be used, such as multiple units or components being combined or integrated into another system, or some features being ignored or not implemented. In addition, the mutual coupling, direct coupling, or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device, or unit, or may be an electrical, mechanical, or other form of connection.

[0120] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments herein.

[0121] In addition, the functional units in the various embodiments herein may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0122] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this article is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this article. The aforementioned storage medium includes: various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0123] This article uses specific embodiments to illustrate the principles and implementation methods of this article. The description of the above embodiments is only used to help understand the methods and core ideas of this article. At the same time, for those skilled in the art, based on the ideas of this article, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation to this article.

Claims

1. A parameter selection method based on the migration law of gas injection in condensate gas reservoirs, characterized in that: The method comprises: Constructing a mathematical model of injected fluid flow and diffusion according to the injection condition set; Numerically quantifying the mathematical model of the flow and diffusion of the injected fluid to obtain the relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Peclet curve; Constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir, and conducting a condensate gas reservoir simulation experiment based on the physical simulation model and the injection conditions to obtain a simulation result; According to the simulation results, verify and fit the relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Péclet number, and determine the breakthrough time calculation formula; Using the injection parameter set, a gas injection experiment is performed on the condensate gas reservoir based on the physical simulation model of the injected fluid displacing the condensate gas reservoir, and using the breakthrough time calculation formula, the breakthrough time of the gas injection experiment of the condensate gas reservoir corresponding to each group of injection parameter sets is calculated; The injection parameter set corresponding to the gas injection experiment of the condensate gas reservoir with the shortest breakthrough time is determined as the optimal injection parameter.

2. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 1 is characterized in that: The injection condition set includes the fluid velocity, viscosity, diffusion coefficient, concentration, and flow function of the injected fluid. Constructing the injected gas flow diffusion model based on the injection condition set includes: A kinetic equation of the injected fluid is constructed based on the fluid velocity, viscosity and diffusion coefficient of the injected fluid; According to the concentration and flow rate function of the injected fluid, the convection-diffusion equation of the fluid concentration is constructed; Performing dimensionless analysis on the kinetic equation and the convection-diffusion equation; The flow variables in the kinetic equation and diffusion equation after dimensionless analysis are subjected to Hartley transformation to obtain a mathematical model of the flow and diffusion of the injected gas.

3. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 2 is characterized in that: According to the fluid velocity of the injected fluid, the viscosity of the injected fluid and the diffusion coefficient, the kinetic equation of the injected fluid is constructed, including the kinetic equation represented by the following formula: Wherein, p'=p / (μ1·D·K-1), represents pressure, U represents velocity field of injected fluid; D represents diffusion coefficient tensor, μ'=μ / μ1 represents dimensionless fluid viscosity, u'=u / U represents dimensionless fluid velocity, μ1· represents, K represents permeability of injected fluid, μ represents fluid viscosity; According to the concentration and flow function of the injected fluid, the convection-diffusion equation of the fluid concentration is constructed, including the convection-diffusion equation expressed by the following formula: Where c represents the concentration of the injected fluid, ψ is the flow rate function, x and y represent the two-dimensional horizontal and vertical coordinates, t' represents the dimensionless time, and c' represents the dimensionless concentration.

4. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 3 is characterized in that: The mathematical model of the flow and diffusion of the injected fluid is numerically quantified to obtain the relationship curve between the injected gas breakthrough time, mobility ratio and Péclet number, including: Numerically solving a mathematical model of the flow and diffusion of the injected fluid, and respectively determining a viscosity index diameter of the mathematical model of the flow and diffusion of the injected fluid at a constant diffusion coefficient at different times and a viscosity index diameter at a constant mobility ratio at different times; According to the viscosity index diameter under constant diffusion coefficient at different times and the viscosity index diameter under constant mobility ratio at different times, the relationship curve between breakthrough time, mobility ratio and Péclet number is determined.

5. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 1 is characterized in that: The physical simulation model for injecting fluid to displace condensate gas reservoirs includes: Determine the condensate gas required for physical simulation based on the on-site well flow composition; According to the status of the on-site wells, based on the principle of similarity between gravity and displacement force ratio, the physical simulation injection-production pressure difference is determined; Determine the injection rate of the injected fluid based on the injection-production pressure difference and Darcy's formula; Select different gas injection methods, injection fluid types, injection timing, injection pressure, and injection speed to complete the construction of the physical simulation model.

6. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 5 is characterized in that: The dynamic equation considering gravity is as follows: Among them, x and y are the horizontal and vertical coordinates of the fluid in the two-dimensional coordinates; u represents the injection velocity, g represents gravity, μ / K represents the fluid mobility, P represents the pressure, μ represents the fluid viscosity, K represents the permeability of the injected fluid, ρ represents the fluid density, and g represents the acceleration due to gravity.

7. The parameter selection method based on the migration law of gas injection in condensate gas reservoir according to claim 1 is characterized in that: According to the simulation results and the relationship curve, the relationship between the fitting breakthrough time, mobility ratio and Péclet number was verified, and the breakthrough time calculation formula was determined: The relationship between dimensionless breakthrough time, mobility ratio and Péclet number is determined by fitting using the following formula: t BT =e 0.793419 ×e -0.231092R ×Pe 0.899608 ; where t BT represents dimensionless breakthrough time; R represents mobility ratio, P e represents the Péclet number; The breakthrough time is determined according to the following formula: Among them, t BT represents the dimensionless breakthrough time; t represents the breakthrough time, D represents the diffusion coefficient tensor, and U represents the injection velocity.

8. A parameter selection device based on the migration law of gas injection in condensate gas reservoir, characterized in that: The device comprises: A mathematical model building unit, used to build a mathematical model of flow diffusion of the injected fluid according to the injection conditions, wherein the injection conditions include: properties of the injected medium, diffusion convection of the injected fluid; A relationship curve determination unit, used for digitizing the mathematical model of the flow and diffusion of the injected fluid, and obtaining the injection gas breakthrough time and mobility ratio and the Peclet relationship curve; A physical simulation model building unit is used to build a physical simulation model for injecting fluid to displace a condensate gas reservoir, and to perform a condensate gas reservoir experiment under the injection conditions based on the physical simulation model to obtain a simulation result; A breakthrough time calculation unit, used to verify and fit the mobility ratio and the Péclet number according to the simulation result and the relationship curve, and determine a breakthrough time calculation formula; An experimental unit, used to perform a gas injection experiment in a condensate gas reservoir using an injection parameter set, and to calculate the breakthrough time of the gas injection experiment in the condensate gas reservoir corresponding to each injection parameter set using the breakthrough time calculation formula; The optimal injection parameter determination unit is used to determine the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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